Natural f-DP filters are invalid for adaptive composition, but a CLT-based GDP approximation gives tighter bounds than RDP for subsampled Gaussians when sampling rate is near 0 or 1.
Corollary A.9.Let HM be the privacy profile of a mechanism M, and let fM be the corresponding tightest trade-off function such thatMisf M-DP
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$f$-Differential Privacy Filters: Validity and Approximate Solutions
Natural f-DP filters are invalid for adaptive composition, but a CLT-based GDP approximation gives tighter bounds than RDP for subsampled Gaussians when sampling rate is near 0 or 1.